diff --git a/sort.py b/sort.py
index db2f6dc..089ec1b 100644
--- a/sort.py
+++ b/sort.py
@@ -25,8 +25,7 @@ matplotlib.use('TkAgg')
 import matplotlib.pyplot as plt
 import matplotlib.patches as patches
 from skimage import io
-#from sklearn.utils.linear_assignment_ import linear_assignment
-import lap
+
 import glob
 import time
 import argparse
@@ -34,6 +33,19 @@ from filterpy.kalman import KalmanFilter
 
 np.random.seed(0)
 
+
+def linear_assignment(cost_matrix):
+  try:
+    import lap
+    _, x, y = lap.lapjv(cost_matrix, extend_cost=True)
+    return np.array([[y[i],i] for i in x if i >= 0]) #
+  except ImportError:
+    from scipy.optimize import linear_sum_assignment
+    x, y = linear_sum_assignment(cost_matrix)
+    return np.array(list(zip(x, y)))
+
+  
+
 @jit
 def iou(bb_test, bb_gt):
   """
@@ -155,14 +167,11 @@ def associate_detections_to_trackers(detections,trackers,iou_threshold = 0.3):
   if min(iou_matrix.shape) > 0:
     a = (iou_matrix > iou_threshold).astype(np.int32)
     if a.sum(1).max() == 1 and a.sum(0).max() == 1:
-        #matrix is  #TODO(this doesnt provide much gains)
         matched_indices = np.stack(np.where(a), axis=1)
     else:
-      _, x, y = lap.lapjv(-iou_matrix, extend_cost=True)
-      matched_indices = np.array([[y[i],i] for i in x if i >= 0]) #
+      matched_indices = linear_assignment(-iou_matrix)
   else:
     matched_indices = np.empty(shape=(0,2))
-  #matched_indices = linear_assignment(-iou_matrix)
 
   unmatched_detections = []
   for d, det in enumerate(detections):
@@ -271,6 +280,7 @@ if __name__ == '__main__':
       exit()
     plt.ion()
     fig = plt.figure()
+    ax1 = fig.add_subplot(111, aspect='equal')
 
   if not os.path.exists('output'):
     os.makedirs('output')
@@ -290,7 +300,6 @@ if __name__ == '__main__':
         total_frames += 1
 
         if(display):
-          ax1 = fig.add_subplot(111, aspect='equal')
           fn = 'mot_benchmark/%s/%s/img1/%06d.jpg'%(phase, seq, frame)
           im =io.imread(fn)
           ax1.imshow(im)
@@ -313,7 +322,7 @@ if __name__ == '__main__':
           plt.draw()
           ax1.cla()
 
-  print("Total Tracking took: %.3f for %d frames or %.1f FPS" % (total_time, total_frames, total_frames / total_time))
+  print("Total Tracking took: %.3f seconds for %d frames or %.1f FPS" % (total_time, total_frames, total_frames / total_time))
 
   if(display):
     print("Note: to get real runtime results run without the option: --display")